PROJECTSUMMARY This P50 application proposes a novel interdisciplinary center at the intersection of behavioral economics and implementation science in pursuit of improving mental health service delivery. The University of Pennsylvania offers a unique environment in which to conduct this paradigm-shifting work, given our expertise in implementation science, mental health services, and behavioral economics represented by the three PIs (Beidas, Mandell, Volpp) and their respective centers (Center for Mental Health Policy and Services Research and Center for Health Incentives and Behavioral Economics). This application also leverages our 30-year relationship with Philadelphia's publicly funded agencies, particularly the Department of Behavioral Health and Intellectual Disability Services. To advance this research agenda, we propose three projects that use behavioral economics approaches to implement evidence-based practices. The projects address the multi-level nature of the implementation process (organization, practitioner, client) by having each project target one of those levels. Project 1 (Marcus, Olfson, Volpp) leverages decision-making biases to compare ways to incentivize adherence to anti- depressant medications in the first six weeks of treatment among adults newly diagnosed with depression. Pro- ject 2 (Mandell, Pellecchia) applies normative pressure and social status to increase data collection among community mental health workers treating children with autism. Project 3 (Beidas, Williams) explores how behavioral economics can be used to design behavioral-economics based implementation strategies that target administrators whose agencies are using evidence-based practices. The projects are supported by a Methods Core that provides expertise in implementation science, behavioral economics, stakeholder engagement, participatory design, measurement, and associated statistical approaches. The Methods Core addresses three major challenges to implementation science in mental health: designing theory-based implementation strategies, measuring putative causal mechanisms in implementation, and testing causality through statistical tests of mediation and moderation in multi-level models. These challenges also will be directly tested in our projects. First, we will test and refine stakeholder-partnered mechanism for designing implementation strategies (e.g., discrete choice experiments; innovation tournaments). Second, we will combine measurement strategies from behavioral economics and implementation science to test measures that capture the psychological biases and organizational factors that we hypothesize are mechanisms of implementation. Third, we will develop sophisticated strategies for testing mediation and moderation in multi-level study designs (clients within practitioners within agencies). This trifecta will lead to dramatic improvements in our knowledge of what causes successful implementation, what variables moderate and mediate the effects of those causal factors, and how best to leverage this knowledge to increase quality of care and outcomes for individuals.